score-based

Proposes GRACE, a method that combines constraint-based skeleton with gated refinement using L0 regularization for efficient and accurate causal edge discovery in high-dimensional time series. It outperforms existing methods in F1 and speed, demonstrated on synthetic and real-world river flow data.

This paper introduces score-based methods for causal discovery in the presence of latent variables, offering theoretical guarantees of consistency and score equivalence, and unifies several constraint-based approaches.